Approximation algorithms for campaign management

Authors:
Edith Elkind;Piotr Faliszewski
Affiliations:
School of Physical and Mathematical Sciences, Nanyang Technological University, Singapore;Department of Computer Science, AGH Univ. of Sci. and Tech., Kraków, Poland
Venue:
WINE'10 Proceedings of the 6th international conference on Internet and network economics
Year:
2010

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Abstract

We study electoral campaign management scenarios in which an external party can buy votes, i.e., pay the voters to promote its preferred candidate in their preference rankings. The external party's goal is to make its preferred candidate a winner while paying as little as possible. We describe a 2-approximation algorithm for this problem for a large class of electoral systems known as scoring rules. Our result holds even for weighted voters, and has applications for campaign management in commercial settings. We also give approximation algorithms for our problem for two Condorcet-consistent rules, namely, the Copeland rule and maximin.